module `onnxrt.ops_cpu.op_squeeze`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_squeeze

Runtime operator.

Classes#

class	truncated documentation
`Squeeze_1`
`Squeeze_11`
`Squeeze_13`	Squeeze ======= Remove single-dimensional entries from the shape of a tensor. Takes an input axes with a list of axes …
`Squeeze_13`	Squeeze ======= Remove single-dimensional entries from the shape of a tensor. Takes an input axes with a list of axes …

Properties#

property	truncated documentation
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`__init__`
`_infer_shapes`
`_infer_shapes`
`_infer_shapes`
`_infer_shapes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_types`
`_infer_types`
`_infer_types`
`_infer_types`
`_run`
`_run`
`_run`
`_run`

Documentation#

Runtime operator.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze#: alias of mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze_13

class mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze_1(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnaryNum

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

__init__(onnx_node, desc=None, **options)#

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x)#

Returns the same shape by default.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(x)#

Returns the same type by default.

source on GitHub

_run(data)#

Should be overwritten.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze_11(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze_1

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_squeeze.Squeeze_13(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Remove single-dimensional entries from the shape of a tensor. Takes an input axes with a list of axes to squeeze. If axes is not provided, all the single dimensions will be removed from the shape. If an axis is selected with shape entry not equal to one, an error is raised.

Inputs

Between 1 and 2 inputs.

data (heterogeneous)T: Tensors with at least max(dims) dimensions.
axes (optional, heterogeneous)tensor(int64): List of integers indicating the dimensions to squeeze. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(data).

Outputs

squeezed (heterogeneous)T: Reshaped tensor with same data as input.

Type Constraints

T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(bfloat16), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128): Constrain input and output types to all tensor types.

Version

Onnx name: Squeeze

This version of the operator has been available since version 13.

Runtime implementation: Squeeze

Parameters